Learn how to analyze data using Python and/or R programming languages (via Zoom)

December 21, 2021

Learn essential programming skills during the R workshop series and the Python workshop series. Attend any or all of the sessions. Brought to you as a part of the UW Libraries Graduate Support workshop series. Open to all UW-Madison students, faculty, and staff.

Location:  Online via Zoom; connection information will be sent in advance.

The R Series

*Registration required.  Registration is by workshop, not for the entire series. See links below to register for individual workshops.  Sessions are filling up fast!

To find out more about this series, see: https://researchguides.library.wisc.edu/R

Friday, February 4, 10am-12pm
R Programming:  R Basics
Register:  https://go.wisc.edu/29027x

Learning how to code can be intimidating, but will save you time and effort in the long run. This workshop will cover the basics of R programming. By the end of this session, you will be able to create variables, use pre-defined functions, understand data types and load and inspect a dataset using RStudio. This workshop is geared toward programming novices, so no previous experience is required.

Friday, February 11, 10am-12pm
R Programming:  R Basics (repeat)
Register: https://go.wisc.edu/h8k21p

This workshop is an exact repeat of the February 4th “R Programming: R Basics” workshop (see above).

Friday, February 18, 10am-12pm
R Programming:  Data Wrangling
Register:  https://go.wisc.edu/djuk5w

Data is rarely perfect out of the box. This workshop will cover how to manipulate datasets using an R package called dplyr. After this session, you will be able to select rows and columns, add new columns, remove missing data and create summary tables of your data. A basic working knowledge of R and R studio (functions, operators, data types) would be helpful for you to get the most out of this session.

Friday, February 25, 10am-12pm
R Programming:  Visualization
Register: https://go.wisc.edu/ef68qt

So now you’re familiar with R, but want to do more with your plots than the base graphics package. This workshop will show you how to use the ggplot2 package in R. After this session, you will be able to create a variety of plot types, alter their aesthetics, and create custom themes. A working knowledge of R and R studio and dplyr would be helpful for you to get the most out of this session.

Friday, March 4, 10am-12pm
R Programming:  Reports
Register: https://go.wisc.edu/i38zj3

Documenting your analysis in a way that is understandable to a colleague (or yourself 3 months later) can be challenging. One way to make reports more readable, even by people who don’t code, is to alternate human readable text with machine readable code. This workshop will cover creating reproducible reports of this type using knitr. After this session, you will be able to create R markdown documents, add formatted text and executable code blocks, and render the R markdown document into a final report.

The Python Series

*Registration required.  Registration is by workshop, not for the entire series. See links below to register for individual workshops.  Sessions are filling up fast!

To find out more about this series, see: https://researchguides.library.wisc.edu/python

Tuesday, February 1, 10am-12pm
Python Programming:  Introduction
Register:  https://go.wisc.edu/j264my

This workshop is for the absolute beginner wanting to slowly walk through the process of getting started with Python, a programming language commonly used for data analysis.  We’ll work through installation and setup of some helpful software and introduce basic concepts and terminology used in Python.  Finally, we’ll work together to create your first simple but useful program!

Tuesday, February 8, 10am-12pm
Python Programming:  Introduction (repeat)
Register: https://go.wisc.edu/j1873x

This workshop is an exact repeat of the February 1 “Python: Introduction” workshop (see above).

Tuesday, February 15, 10am-12pm
Python Programming:  Loops, lists, and functions
Register:  https://go.wisc.edu/e8z234

This workshop will take a deeper dive into Python, covering essential topics such as automating tasks using loops, lists, and functions.

Tuesday, February 22, 10am-12pm
Python programming:  Spreadsheets and data wrangling with pandas
Register:  https://go.wisc.edu/au8b66

Real-world data can be messy.  This workshop will cover a range of topics related to organizing and manipulating spreadsheet data for more effective analysis. We’ll use pandas, a popular and free data analysis library written for Python.

Tuesday, March 1, 10am-12pm
Python Programming:  Data Visualization with seaborn
Register:  https://go.wisc.edu/x4s20q

In this workshop, we will explore different methods and tools for visualizing data using Python. We’ll use seaborn, a popular and free data visualization library written for Python.

Workshop Instructors

Trisha Adamus

Trisha Adamus is a Health Sciences Librarian at University of Wisconsin-Madison (Ebling Library) specializing R programming and data management.

Questions? adamus@wisc.edu

Dave Bloom

Dave Bloom is a Science and Engineering Librarian at University of Wisconsin-Madison specializing research data management.

Questions? david.bloom@wisc.edu

Sarah Graves

Sarah Graves is a Environmental Observation and Informatics Program Coordinator for The Nelson Institute for Environmental Studies, University of Wisconsin-Madison.

Andrew Maule

Jennifer Patiño

Jennifer Patiño is the Data and Digital Scholarship Diversity Resident Librarian, University of Wisconsin-Madison.

Erwin Lares

Erwin Lares is a PA Research Cyberinfrastructure at University of Wisconsin-Madison.

Casey Schacher

Casey Schacher is a Science and Engineering Librarian at University of Wisconsin-Madison specializing Python programming and data management.

Questions? casey.schacher@wisc.edu

Heather Shimon

Heather Shimon is a Science and Engineering Librarian at University of Wisconsin-Madison specializing research data management.

Questions? heather.shimon@wisc.edu 

Sarah Stevens

Sarah Stevens is a Data Science Hub Facilitator for the Data Science Institute, University of Wisconsin-Madison.

Sailendharan Sudakaran

Sailendharan Sudakaran is the Madison Microbiome Hub Manager / Multi Omics Hub Coordinator , University of Wisconsin-Madison.

Helpers: 

Imraan Alas, University of Wisconsin-Madison

Mele Avilla, University of Wisconsin-Madison

Dandi Chen, University of Wisconsin-Madison

Nina Desianti, University of Wisconsin-Madison

Chris Endemann, Data Science Hub Facilitator, University of Wisconsin-Madison

Steve Goldstein, University of Wisconsin-Madison

Corey Halpin, Software Engineer for Internet Scout, University of Wisconsin-Madison

Summera Fahmi Khan, University of Wisconsin-Madison

Hannah Olson-Williams, University of Wisconsin-Madison

Bethany Moore, University of Wisconsin-Madison

Tomoko Okada, University of Wisconsin-Madison

Zekai Otles, Systems Administrator, Clinical & Health Informatics Institute, University of Wisconsin-Madison

Clare Michaud, Data Science Hub Facilitator, University of Wisconsin-Madison

Mary Murphy, Wrap Database Administrator, Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison

Madeline Reed, University of Wisconsin-Madison

Dylan Schoemaker, University of Wisconsin-Madison

Qiuyu Yang, University of Wisconsin-Madison